
SmallFP & ClojureTRE: Interactive, Functional, GPU Accellerated Programming in Clojure
September 11, 2018
I'm presenting a talk at SmallFP conference in Helsinki, Finland. Here are the slides.

Neanderthal vs ND4J  vol 4  Fast Vector Broadcasting in Java, CPU and CUDA
July 25, 2018
In which we implement our own vector broadcasting function that matches the performance of Nd4j's optimized one and even surpasses it on the GPU.

Fast Function Currying in Clojure (Without Macros)
July 8, 2018
Fluokitten 0.8.0 just got released. I significantly improved the performance of existing currying functionality. Here's a walkthrough.

Map and Reduce Primitive Arrays Without Clojure Macros
July 5, 2018
Fluokitten 0.7.0 just got released. Now it supports Java arrays. A brief walktrough.

Neanderthal vs ND4J  vol 3  Clojure Beyond the Fast Native MKL Backend
June 29, 2018
Some free time fell into my lap, and I decided to continue helping the DL4J team at Skymind improve ND4J. This is a direct continuation of Vol 2.

Neanderthal vs ND4J  vol 2  The Same Native MKL Backend, 1000 x Speedup
June 28, 2018
Mercenary work have been finished ahead of time; a handful of time to spare. Time for free software! More Neanderthal vs ND4J comparison, then?

Neanderthal vs ND4J  vol 1  Native performance, Java and CPU
June 22, 2018
Today, Java has a choice of a few well maintained libraries that can use Intel's MKL for fast native operations. MKL is basically as fast as you can get today on the CPU. The reasoning is that, since two libraries use MKL, they should squeeze the same amount of juice out of it. It's not quite like that.

Out of the box support for TensorFlow and PyTorch for Clojure has landed in Neanderthal
April 1, 2018
Out of the box support for TensorFlow and PyTorch for Clojure has landed in Neanderthal.

Interactive GPU Programming  Part 3  CUDA Context Shenanigans
March 1, 2018
All communication with the GPU takes place in a context. Context is an analogous to a CPU program. It sets the environment for the particular GPU we want to use in the computations. Simple on the surface, it is, unfortunately, incidentally complex due to early CUDA legacy. So what? We have to deal with that, so, instead of complaining, we'll see how to tame it...

Interactive GPU Programming  Part 2  Hello OpenCL
February 7, 2018
This is really the same article as Part 1  Hello CUDA, but with the focus on OpenCL, so I'll skip most of the narration and just show you the code.

Neanderthal and friends support CUDA 9, Java 9, and Clojure 1.9
January 17, 2018
Uncomplicate libraries have just got a nice update and are ready for the latest underlying platform releases. CUDA 9, Java 9, and Clojure 1.9.

Interactive GPU Programming  Part 1  Hello CUDA
January 17, 2018
Today, fast number crunching means parallel programs that run on Graphical Processing Units (GPUs). Thanks to the recent highly publicized deep learning and artificial intelligence advances, everyone has heard about Nvidia's CUDA  an environment and set of C++ oriented tools that transform your GPU card into a sort of a desktop supercomputer. Yes, that is interesting, and we want to get in! But we would also like an interactive environment that is easy to set up and easy to play with, without a loss of power or performance.

Clojure Numerics, Part 6  More Linear Algebra Fun with Least Squares
December 27, 2017
This time, we look at a few important variants of the least squares problem. Least squares with equality constraints, and generalized least squares. They show how we can solve problems where there is some norm to be minimized with additional constraints to be satisfied. A very cool and useful thing to know.

Clojure Numerics, Part 5  Orthogonalization and Least Squares
October 17, 2017
How to solve linear systems that have many solutions, or those that have no solutions at all? That's the theme for a thick math textbook, of course, but from the programmer's point of view, we are interested in the practical matters, so I'll stick to the main point. When I have less equations than there are unknowns, or I have too many equations, what can I do in Clojure to make those unknowns known? Which functions do I call?

Clojure Numerics, Part 4  Singular Value Decomposition (SVD)
October 4, 2017
Today's article is a short one. Not because Singular Value Decomposition (SVD) is not important, but because it is so ubiquitous that we'll touch it in other articles where appropriate. The goal of this article is to give an overview and point to Neanderthal's functions that work with it. When you see SVD in the literature you read, you'll know where to look for the implementation; that's the idea.

What's nice about Clojure numerical computing with new Neanderthal 0.16.0
September 18, 2017
I've spent some quality time with my Emacs sipping some CIDER, and it is a good moment to introduce the release 0.16.0 of Neanderthal, the linear algebra and numerical computing library for Clojure. The time spent over the summer on refactoring the foundations for 0.15.0, pays the dividends now. It has been much easier for me to add many new features and polish the old ones. And the best news is that I expect this to continue giving for the upcoming releases.

Clojure Numerics, Part 3  Special Linear Systems and Cholesky Factorization
September 18, 2017
In the last article we have learned to solve general linear systems, assuming that the matrix of coefficients is square, dense, and unstructured. We have also seen how computing the solution is much faster and easier when we know that the matrix is triangular. These are pretty general assumptions, so we are able to solve any welldefined system. We now explore how additional knowledge about the system can be applied to make it faster. The properties that we are looking for are symmetry, definiteness, and bandedness.

Clojure Numerics, Part 2  General Linear Systems and LU Factorization
September 7, 2017
Solving systems of linear equations is a staple food of linear algebra. It can be applied as a part of many machine learning tasks, although it is not always obvious to spot the opportunity. Here, we explore how triangular systems are the foundation that we need to internalize well. We concentrate on computational details, and transformations of general systems to triangular systems . Neanderthal offers many functions to help us in this quest.

Neanderthal 0.15.0 Released  Many more specialized matrix data structures in Clojure
September 1, 2017
The new release of Neanderthal, the fast Clojure one stop shop for linear algebra and matrix computations at top speed on Intel and AMD CPU's, and both Nvidia and AMD GPU's has just been released to Clojars.

Setting up Neanderthal  High Performance Clojure Easy as 1,2,3
August 18, 2017
This is a flash post, written after having a sudden thought while reading a book totally unrelated to Clojure. How hard (or easy) is it to start with Neanderthal? This is only a rhetorical question, since I am not interested in _your_ answer. I'm interested in your opinion on another matter. Here it is.

Clojure Numerics, Part 1  Use Matrices Efficiently
June 26, 2017
It's time to step back from theory and look a bit more into implementation details of all that matrix stuff. In this post, I give an overview of data structures that I use to represent matrices in Clojure, methods to manipulate them, and a few tips and tricks that you can use to make your code fast.

Clojure Linear Algebra Refresher (4)  Linear Transformations
June 15, 2017
Now that we got ourselves acquainted with matrix transformations, the next obvious step is to generalize our knowledge with linear transformations.

Clojure Linear Algebra Refresher (3)  Matrix Transformations
June 13, 2017
A Clojure programmer will immediately feel at home with linear transformations  functions are also transformations. Linear transformations preserve the mathematical structure of a vector space. Just like functions define transformations, matrices define a king of linear transformations  matrix transformations. I often see programmers using matrices and vectors as dumb data structures and writing their own loops, or accessing elements one by one in a haphazard fashion. Matrices are useful data structures, but using them as transformations is what really gives them power. This is something that is very well understood in computer graphics, but is often neglected in other areas.

Clojure Linear Algebra Refresher (3)  Matrix Transformations
June 13, 2017
A Clojure programmer will immediately feel at home with linear transformations  functions are also transformations. Linear transformations preserve the mathematical structure of a vector space. Just like functions define transformations, matrices define a king of linear transformations  matrix transformations. I often see programmers using matrices and vectors as dumb data structures and writing their own loops, or accessing elements one by one in a haphazard fashion. Matrices are useful data structures, but using them as transformations is what really gives them power. This is something that is very well understood in computer graphics, but is often neglected in other areas.

Clojure Linear Algebra Refresher (2)  Eigenvalues and Eigenvectors
June 6, 2017
I stumble upon eigenvectors and eigenvalues regularly when reading about machine learning topics. They seem to be important. They are not introduced in those texts, though, so you might be scratching your head wondering how the authors got the idea in the first place to use them and why. Luckily, they are introduced soon enough in linear algebra textbooks, and they are available at highspeed in Clojure via Neanderthal, that we should be able to at least try them out easily, and then build upon that knowledge fearlessly when we encounter them in the wild.

Clojure Linear Algebra Refresher (1)  Vector Spaces
June 3, 2017
This article is a starting article in a series that is going to briefly skim through a good engineering textbook on linear algebra, making notes that help you relate that material to the Clojure code.

CUDA and cuBLAS GPU matrices in Clojure
May 20, 2017
The new release of Neanderthal is here! The highlight of 0.11.0 is the new CUDA/cuBLAS based engine. The highperformance Clojure matrix library now supports all 3 major choices that you'd want to crunch those billions of numbers with  CPU, CUDA GPU on Nvidia, and OpenCL GPU on AMD, or other accellerators. Let's se why this new stuff is important (and it really is!).

Neanderthal 0.9.0 released  Clojure's highperformance computing story is getting into shape
March 31, 2017
Today, I have the pleasure to announce the new release of Neanderthal, the highperformance Clojure matrix library, which brings some important major improvements, and beats the path to even better stuff that will follow in subsequent versions. Let's explore major stuff (and also see some code :)

Neanderthal 0.9.0 with major improvements is around the corner
March 22, 2017
The upcoming version of Neanderthal, the library for vector and matrix computations in Clojure, brings improvements to Clojure's numerical computing capabilities that are so important, that I think there's no harm in talking about them in advance. If you like what you're about to read, you won't have to wait for long, since the implementation is mostly done.

Bayadera = Bayes + Clojure + GPU (slides for my Bob Konferenz 2017 talk)
February 20, 2017
I'll give a talk about Bayadera, Clojure, and Bayes (+ GPU's) in Berlin on February 24. Here are the slides!

Clojure is not afraid of the GPU (video of my EuroClojure2016 talk)
November 18, 2016
The videos for EuroClojure 2016 talks are finally available on YouTube. Here is mine.

Clojure is not afraid of the GPU (slides for my EuroClojure2016 talk)
October 20, 2016
Is there a better way to open the new blog than with a post about my upcoming talk at EuroClojure2016? I decided to put the slides online in advance, so the attendees can relax and enjoy the talk, instead of scraping by to type all the notes and memos.